Recursive Class Connectivity Classification (R3C) Applied to Binary Image Segmentation for Improved Infant Fingerprint Enhancement

Recursive Class Connectivity Classification (R3C) Applied to Binary Image Segmentation for Improved Infant Fingerprint Enhancement

Image enhancement plays a crucial role in infant fingerprint matching, as child-specific characteristics such as smaller finger dimensions and thinner ridge structures often degrade image quality during acquisition. To address these limitations, enrollment typically depends on specialized high-resol...

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Bibliographic Details
Main Authors: Joao Leonardo Harres Dall Agnol, Luiz Fernando Puttow Southier, Jefferson Tales Oliva, Marcelo Teixeira, Rodrigo Minetto, Marcelo Filipak, Dalcimar Casanova, Erick Oliveira Rodrigues
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Binary classification
biometrics
enhancement
fingerprint
infant
newborn
Online Access:https://ieeexplore.ieee.org/document/11106426/
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https://ieeexplore.ieee.org/document/11106426/

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